Approach to the Patient: Pharmacological Therapies for Fracture Risk Reduction in Adults With Osteogenesis Imperfecta
Bibliographic record
Abstract
CONTEXT: Osteogenesis imperfecta (OI) is a genetic disorder characterized by increased bone fragility largely caused by defects in structure, synthesis, or post-translational processing of type I collagen. The effectiveness of medications used for fracture reduction in adults with OI is understudied and practice recommendations are not well established. Drugs currently used to improve skeletal health in OI were initially developed to treat osteoporosis. Oral and intravenous bisphosphonates have been shown to improve bone mineral density (BMD) in adults with OI and are commonly used; however, conclusive data confirming fracture protection are lacking. Similarly, teriparatide appears to increase BMD, an effect that seems to be limited to individuals with type I OI. The role of denosumab, abaloparatide, romosozumab, and estradiol/testosterone in adult OI have not been systematically studied. Anti-sclerostin agents and transforming growth factor-beta antagonists are under investigation in clinical trials. OBJECTIVE: This review summarizes current knowledge on pharmacologic treatment options for reducing fracture risk in adults with OI. METHODS: A PubMed online database search of all study types published in the English language using the terms "osteogenesis imperfecta," "OI," and "brittle bone disease" was performed in June 2022. Articles screened were restricted to adults. Additional sources were identified through manual searches of reference lists. CONCLUSION: Fracture rates are elevated in adults with OI. Although clinical trial data are limited, bisphosphonates and teriparatide may be useful in improving BMD. Further research is needed to develop medications for adults with OI that will lead to definite fracture rate reduction.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.013 | 0.002 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".